Pedestrian Detection Under Micro UAV
XU Bin
LI Ning
ZHU Hanshan
XU Zhi
ZHOU Huiyu
Abstract：The autonomous detection of UAV on ground targets is a crucial issue in intelligent cruise. In recent years,with the rise of deep learning,convolutional neural networks have been tried to apply in the field of target recognition. This paper designs a light-weight convolution neural network model suitable for tiny target detection under UAV. Using UAV real shot samples in the NVIDIA-1080ti platform for verification,the processing speed is up to 82 frames/second.
Keywords：deep learningvisual saliency modelpedestrian detectionmicro UAV
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1935-1940 )